Augmented complex-valued normalized subband adaptive filter: Algorithm derivation and analysis

In this paper, a variable step-size widely linear complex-valued affine projection algorithm (VSS-WLCAPA) is proposed for processing noncircular signals. The variable stepsize (VSS) is derived by minimizing the power of the augmented noise-free a posteriori error vector, which speeds up the convergence and reduces the steady-state misalignment. By exploiting the evolution of the covariance matrix of the weight error vector, we provide insight into the theoretical behavior of the VSS-WLCAPA algorithm. In the analysis, we take into account the dependency between the weight error vector and the noise vector, which is useful for accuracy of the theoretical prediction. To evaluate the mean step-size, the probability density function of the magnitude of the error is derived by employing polar coordinate transformation. Moreover, a special case when the projection order reduces to one is analysed in detail. The presented theoretical analysis is different from existing methodologies for analyzing affine projection algorithms due to the use of the Kronecker product. Simulation results for system identification scenarios demonstrate the merits of the proposed algorithm and verify the accuracy of the theoretical analysis. Wind prediction experiments support the superiority of the proposed VSS-WLCAPA as well.

show abstract

“…Using (35) in (33) and (34), Φ 4 and Φ 5 are calculated. The detailed computation is shown in Appendix A.…”

Section: Define the Augmented Weight Error Vectorw(k)mentioning

confidence: 99%

“…However, this dependency can be important, as argued in [22]. The augmented complex-valued normalized subband adaptive filter (ACNSAF) algorithm was recently put forward in [35], which achieves performance improvement for colored input signals.…”

Section: Introductionmentioning

confidence: 99%

Variable Step-Size Widely Linear Complex-Valued Affine Projection Algorithm and Performance Analysis

Shi

Zhao

Zakharov

et al. 2020

IEEE Trans. Signal Process.

View full text Add to dashboard Cite

show abstract

“…The nc-ACNSAF algorithm can be considered as several independent ACNSAF algorithms updating simultaneously. A more detailed description of ACNSAF algorithm can be found in [32].…”

Section: B Sd-acnsaf Algorithmmentioning

confidence: 99%

Diffusion ACNSAF Algorithm for Secure Distributed Estimation Under Complex-Valued Attacks

Wen

Zhang

et al. 2020

IEEE Access

Self Cite

View full text Add to dashboard Cite

“…T HE adaptive filtering algorithms have been extensively utilized in a variety of practical applications, such as active noise control (ANC) [1]- [3], acoustic echo cancelation (AEC) [4], [5], and noise cancelation [6]. How to choose or construct an appropriate cost function is a key issue for adaptive filtering algorithm.…”

Section: Introductionmentioning

confidence: 99%

Generalized Minimum Error Entropy for Adaptive Filtering

He,

Wang,

Peng

et al. 2021

Preprint

View full text Add to dashboard Cite

Error entropy is a important nonlinear similarity measure, and it has received increasing attention in many practical applications. The default kernel function of error entropy criterion is Gaussian kernel function, however, which is not always the best choice. In our study, a novel concept, called generalized error entropy, utilizing the generalized Gaussian density (GGD) function as the kernel function is proposed. We further derivate the generalized minimum error entropy (GMEE) criterion, and a novel adaptive filtering called GMEE algorithm is derived by utilizing GMEE criterion. The stability, steadystate performance, and computational complexity of the proposed algorithm are investigated. Some simulation indicate that the GMEE algorithm performs well in Gaussian, sub-Gaussian, and super-Gaussian noises environment, respectively. Finally, the GMEE algorithm is applied to acoustic echo cancelation and performs well.

show abstract

Augmented complex-valued normalized subband adaptive filter: Algorithm derivation and analysis

Cited by 29 publications

References 24 publications

Variable Step-Size Widely Linear Complex-Valued Affine Projection Algorithm and Performance Analysis

Variable Step-Size Widely Linear Complex-Valued Affine Projection Algorithm and Performance Analysis

Diffusion ACNSAF Algorithm for Secure Distributed Estimation Under Complex-Valued Attacks

Generalized Minimum Error Entropy for Adaptive Filtering

Contact Info

Product

Resources

About